Senior Data Scientist

Candidates must possess a B.S., M.S., or Ph.D. in Engineering, Data Science, Computer Science, Math, Statistics, or a related quantitative field, along with 5+ years of hands-on experience as a Data Scientist with a strong focus on advanced analytics and machine learning. Required skills include exceptional analytical abilities for large, complex datasets, deep expertise in temporal feature extraction from time-series data, and strong understanding and practical experience with geospatial data analysis, feature engineering, and spatial reasoning. Proficiency in designing and implementing algorithms for classification, clustering, and feature selection, expertise in machine learning algorithms including deep learning for sequential and spatial data, and strong programming skills in Python with extensive experience in data science libraries are essential. Experience with big data frameworks like PySpark for distributed data processing is also required, along with excellent problem-solving skills, meticulous focus on model validation, robustness, and accuracy, ability to work independently, manage priorities, and thrive in a fast-paced, collaborative environment. Strong communication and presentation skills to articulate complex technical concepts to diverse audiences are necessary.